Customers purchase a large number of goods in shopping environments. Retailers often strive to gather accurate information concerning the product presentation within a shopping environment to more effectively market their goods, and thereby increase sales. One type of information that is valuable to retailers is the precise location of products within their retail environments. Several challenges exist to gathering accurate product location data.
One prior method for identifying product locations involves an employee walking through a shopping environment and scanning product tags on the shelves, etc., for each product located in the shopping environment. The product ID is stored along with position information, and a map of products is generated, which may be referred to as a planogram. One drawback to this method is that human error can result in erroneous planograms. Common errors include skipping products during scanning, and moving products after they have been scanned so that the actual location no longer matches the planogram. Further, scanning by employees takes time and is expensive, in addition to being subject to errors. Thus, current methods suffer from high cost, delay, and inaccuracy. These problems are exacerbated by frequent, planned movement of products by management from one location to another. Further, it will be appreciated that planograms are also created by store management prospectively to instruct employees where to place products, however various issues may arise during actual product placement in which the fulfillment of the planogram-specified product placements may be impossible or impractical, and thus differences may arise between the product placement plan specified in the planogram and the actual product placement in the store.